Distribution of Hyperpolarized Xenon in the Brain Following Sensory Stimulation: Preliminary MRI Findings
Bibliographic record
Abstract
In hyperpolarized xenon magnetic resonance imaging (HP (129)Xe MRI), the inhaled spin-1/2 isotope of xenon gas is used to generate the MR signal. Because hyperpolarized xenon is an MR signal source with properties very different from those generated from water-protons, HP (129)Xe MRI may yield structural and functional information not detectable by conventional proton-based MRI methods. Here we demonstrate the differential distribution of HP (129)Xe in the cerebral cortex of the rat following a pain stimulus evoked in the animal's forepaw. Areas of higher HP (129)Xe signal corresponded to those areas previously demonstrated by conventional functional MRI (fMRI) methods as being activated by a forepaw pain stimulus. The percent increase in HP (129)Xe signal over baseline was 13-28%, and was detectable with a single set of pre and post stimulus images. Recent innovations in the production of highly polarized (129)Xe should make feasible the emergence of HP (129)Xe MRI as a viable adjunct method to conventional MRI for the study of brain function and disease.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".